The week's pick
Reseach Article
Gaussian Fitting Model for Non-Geometric Features in Gesture Recognition System: Analysis Study
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 148 - Number 9 |
| Year of Publication: 2016 |
| Authors: Mokhtar M. Hasan |
10.5120/ijca2016911332
|
Mokhtar M. Hasan . Gaussian Fitting Model for Non-Geometric Features in Gesture Recognition System: Analysis Study. International Journal of Computer Applications. 148, 9 ( Aug 2016), 39-41. DOI=10.5120/ijca2016911332
Abstract
Gesture language is considered as secondary language for most of people and main language for hearing impaired people, it is considered as international non-spoken language that make the understanding between different tongues possible regardless which country is this, it is also considered the first language that can be act for children in which they express they need in a movement. There are vast range of non-geometric features that can applied to recognize specific object, we have applied in this paper novel algorithm by building Gaussian model that covers the area of the hand gesture which may or may not circular area, because of that Gaussian is chosen for any circular or oval shape depending on the presented gesture itself, furthermore, rotation variation has been solved in order to reduce the database size used for training the model, experimental results show a promising outcomes that dominant on the other non-geometric techniques.
References
- Mokhtar M. Hasan, Noor Adnan Ibraheem, “Mixture of GMMs and Mixture of Multiple Histograms for Image Segmentation: A Review”, International Journal of Computer Science, vol. 4 , issue 2, number 2, pp.739-743, July 2016.
- Noor A. Ibraheem, Rafiqul Z. Khan, Mokhtar M. Hasan, “Comparative Study of Skin Color Based Segmentation Techniques”, International Journal of Applied Information Systems (IJAIS), vol. 5 (10): 24-39, USA, August 2013.
- Hasan, M.M., Mishra, P.K., “Direction Analysis Algorithm using Statistical Approaches”, SPIE 4th International Conference on Digital Image Processing, 8334-28, 83340L (2012), Malaysia, April 2012, doi: 10.1117/12.946046.
- J. Mackie ,B. McCane, “Finger Detection with Decision Trees”, University of Otago, Department of Computer Science.
- Jochen Triesch, and Christoph von der Malsburg, “A system for person-independent hand posture recognition against complex backgrounds”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23 (12), pp. 1449-1453, Dec 2011, doi: 10.1109/34.977568.
- Xingyan Li, “Vision Based Gesture Recognition System with High Accuracy”, Department of Computer Science, The University of Tennessee, Knoxville, 2005.
- Agnes Just, Yann Rodriguez, Sebastien Marcel, “Hand Posture Classification and Recognition using the Modified Census Transform”, In Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (AFGR 2006), Southampton , UK, April 2006, doi: 10.1109/FGR.2006.62.
- Simei G. Wysoski, Marcus V. Lamar, Susumu Kuroyanagi , Akira Iwata , “A Rotation Invariant Approach On Static-Gesture Recognition Using Boundary Histograms And Neural Networks”, In Proceedings of the 9th IEEE International Conference on Neural Information Processing (ICONIP '02), Vol. 4, pp. 2137 – 2141, Singapore, Nov, 2002, doi: 10.1109/ICONIP.2002.1199054.
- Ravikiran J, Kavi Mahesh, Suhas Mahishi, Dheeraj R, Sudheender S, and Nitin V Pujari,” Finger Detection for Sign Language Recognition”, Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS 2009), vol. I, Hong Kong, March 2009.
- Jagdish Lal Raheja, Karen Das, and Ankit Chaudhary, “An Efficient Real Time Method of Fingertip Detection”, 7th International Conference on Trends in Industrial Measurements and Automation (TIMA 2011), Chennai, India, Jan 2011, pp. 447-450.
- Sung Kwan Kang, Mi Young Nam ,and Phill Kyu Rhee, “Color Based Hand and Finger Detection Technology for User Interaction”, IEEE International Conference on Convergence and Hybrid Information Technology, 2008, pp. 229-236, doi: 10.1109/ICHIT.2008.292.
- Noor Shaker, M. Abou Zliekha, “Real-time Finger Tracking for Interaction”, IEEE 5th International Symposium on Image and Signal Processing and Analysis (ISPA 2007), Istanbul, 2007, pp. 141-145, doi: 10.1109/ISPA.2007.4383679.
- Noor A. Ibraheem, Mokhtar M. Hasan, Rafiqul Z. Khan, “An Investigation on Gesture Analysis and Geometric Features Extraction”, International Journal of Innovative Research in Computer and Communication Engineering, vol. 3 (1): 387-392, India, January 2015, doi: 10.15680/ijircce.2015.0301037.
- Mokhtar M. Hasan, Pramod K. Mishra, “Real Time Fingers and Palm Locating using Dynamic Circle Templates”, International Journal of Computer Applications, vol. 41 (6): 33-43, USA, March 2012, doi: 10.5120/5547-7615.
- Mokhtar M Hasan, “New Rotation Invariance Features Based on Circle Partitioning”, Journal of Computer Engineering & Information Technology, vol. 2 (2), USA, July 2013, doi: 10.4172/2324-9307.1000108.
- Mokhtar M. Hasan, Pramod K. Mishra, “Features Fitting using Multivariate Gaussian Distribution for Hand Gesture Recognition”, International Journal of Computer Science and Emerging Technologies, vol. 3(2):73-80, UK, April 2012.
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